Application of GemPy to Improve Students' Implicit Creation of Complex Geological Models

Abstract

Understanding subsurface geological structures is a persistent pedagogical challenge in earth science and resource-economics education, owing to the inherent difficulty of visualizing three-dimensional spatial relationships from two-dimensional maps, cross-sections, and borehole logs. This paper examines the application of GemPy, an open-source Python library for implicit three-dimensional structural geological modelling, as a tool for improving students' capacity to construct and interpret complex geological models. GemPy uses an implicit modelling approach, interpolating geological surfaces directly from spatially referenced input data such as orientations and interface points, thereby allowing users to generate, and interactively update, three-dimensional representations of stratigraphic layers, faults, and folds without manual digitization of each geological boundary. Drawing on constructivist and technology-enhanced learning theory, and a qualitative synthesis of geoscience education literature and documented classroom applications of open-source modelling software, this paper argues that GemPy's interactive, code-driven, and probabilistically extensible framework offers particular pedagogical value: it allows students to iteratively test structural hypotheses, visualize the consequences of changing input parameters in real time, and engage directly with the mathematical logic underlying implicit interpolation, rather than treating geological modelling software as an opaque black box. The paper further considers GemPy's relevance to economics and resource-management curricula, where geological structural understanding underpins mineral and hydrocarbon resource valuation. It concludes that structured integration of GemPy into relevant coursework, supported by adequate technical scaffolding, can meaningfully improve students' spatial reasoning and conceptual grasp of subsurface structural complexity, while noting that the tool's Python-based interface presents an initial learning-curve barrier that instructors must actively manage.